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Correlations between pathogen concentration and fecal indicator marker genes in beach environments
Qian Zhang1, Jessica J Eichmiller2, Christopher Staley1
1BioTechnology Institute, University of Minnesota, 1479 Gortner Avenue, St. Paul, MN 55108, United States.
The Science of the Total Environment
|September 7, 2016
Summary
Researchers studied potential pathogens in Duluth, MN beach environments. Escherichia coli and Clostridium perfringens were frequently detected, with varying correlations to fecal indicator genetic markers in water versus sand/sediment.
Area of Science:
- Environmental microbiology
- Molecular biology
- Public health
Background:
- Assessing microbial contamination in recreational waters is crucial for public health.
- Fecal indicator bacteria (FIB) are commonly used to infer contamination, but their reliability can vary.
- Potential pathogens may behave differently in various environmental matrices like water, sand, and sediment.
Purpose of the Study:
- To quantify potential pathogen concentrations in beach water, sand, and sediment.
- To investigate the correlations between potential pathogen markers and FIB genetic markers across different sample types.
- To evaluate the suitability of FIB markers for monitoring beach environments.
Main Methods:
- Microfluidic quantitative PCR (MFQPCR) was employed to analyze samples.
- Nineteen different pathogen marker genes were examined.
- Beach water, sand, and sediment samples from Duluth, MN were analyzed.
Main Results:
- The eaeA gene (Escherichia coli) and plc gene (Clostridium perfringens) were the most frequently detected pathogen markers.
- Positive correlations between potential pathogens and FIB markers were found in beach water and wastewater.
- Correlations were less frequent in sand and sediment samples.
Conclusions:
- The behavior of potential pathogens and FIB markers differs between water and sand/sediment matrices.
- Careful selection of FIB marker genes is necessary for accurate water and sand quality monitoring.
- Environmental factors influence the relationship between pathogens and indicators.

